This presentation outlines several business cases for successfully implementing enterprise knowledge graphs that will provide business value and insight. The presentation explores several different types of knowledge graphs that address varying business cases for knowledge and relationships discovery. The use cases range from serving as the basis of a recommendation engine and a future chatbot application, to allowing financial analysts to discover relationships between data fields across multiple financial forms and data series.

1. COMMON SEMANTIC USE CASES
Yanko Ivanov
Senior KM Consultant
November 5, 2018

2. EK AT A GLANCE
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COMPANY (2016)

3. COMMON SEMANTIC USE CASES

4. RECOMMENDATION ENGINE
The Problem
A large international development bank needed
a better way to disseminate information and
expertise to all of their staff so that projects
would be more efficient and more successful.
Sample questions:
• What is the latest on education in this
country?
• How are these types of infrastructure
projects tackled in other countries?
• What do I need to know on this topic before
my next meeting with this country’s
representative?
The Solution
A semantic hub leveraging a knowledge graph
for all of the relevant people and content within
the organization.
• Knowledge graph that collects the content,
user information, and activities.
• Semantic hub as the central orchestrator of
information flow.
• This information is used to recommend
relevant articles and information when
meetings are scheduled, during searches,
and eventually to power a chat bot.
Taxonomies Ontologies Auto-tagging
Knowledge
Graph

5. HIGH LEVEL ARCHITECTURE
SOCIAL NETWORK
TRENDS
Semantic
Web App
Widget
Service
Chatbot
BANK
EMPLOYEE
KNOWLEDGE
GRAPH
Semantic Hub
Recommendation
Engine

6. DATA MANAGEMENT & ANALYSIS
The Problem
A large US Federal Agency needs a better way
to manage the thousands of data sets that they
use to develop economic models that drive US
policy.
Currently, there is no way to know what data
sets are owned, how often they are used and
how different data sets relate to one another.
They need a tool that will allow them to better
understand the relationships between data
elements and how others use the data.
The Solution
We are working with the agency to design an
ontology that captures data sets, data
elements, how they relate to one another, and
information about how they are used. This
information is stored in a triple store that sits
behind a custom web application.
The result will be a semantic search application
that allows economists to see data sets, their
data elements and how they relate to one
another. We also capture a log of usage so that
the agency can better negotiate deals with data
vendors.
Taxonomies Ontologies
Knowledge
Graph

7. AUTO-TAGGING AND SEARCH
The Problem
The US Veterans Administration needed a
better way to manage the content on their
PTSD website.
The site has thousands of scholarly articles that
need to be tagged with a deep medical
taxonomy (of over 2000 terms) so that site
users can quickly find the information they need
to improve their quality of life.
The Solution
EK worked with the VA team to learn more
about their internal processes for collecting and
tagging content for search.
The new system has a taxonomy and auto-
tagging tool that analyzes every piece of
content as it is entered into the system. This
automation cuts the content management
process in half and improves the accuracy of
tagging.
Taxonomies Auto-tagging

8. WE’LL BE ANSWERING QUESTIONS NOW
Q A&
THANKS FOR LISTENING
Q & A SESSION

9. CONTACT ME
YANKO IVANOV
yivanov@enterprise-knowledge.com
https://www.linkedin.com/in/yankoivanov/
@YankoKIvanov